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2019
What Drives Merger Waves? A Study of the SevenHistorical Merger Waves in the U.S.Katherine Ching
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Recommended CitationChing, Katherine, "What Drives Merger Waves? A Study of the Seven Historical Merger Waves in the U.S." (2019). Scripps SeniorTheses. 1294.https://scholarship.claremont.edu/scripps_theses/1294
WHAT DRIVES MERGER WAVES?
A STUDY OF THE SEVEN HISTORICAL MERGER WAVES IN THE
U.S.
by
KATHERINE E. CHING
SUBMITTED TO SCRIPPS COLLEGE IN PARTIAL
FULFILLMENT OF THE DEGREE OF BACHELOR OF ARTS
PROFESSOR VAN HORN
PROFESSOR BATTA
DECEMBER 14, 2018
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ABSTRACT
Historically, merger and acquisition (or M&A) activity has occurred in cyclical
patterns, forming what are known as “merger waves.” To date, there have been a total of
seven waves. Though it is widely acknowledged that merger waves exist, there is no
consensus on what drives these waves. Through both qualitative and quantitative analysis,
this paper aims to determine the causes of merger waves and looks at those causes through
two different lenses: the neoclassical view, which states that economic shocks cause merger
waves, and the behavioral view, which states that increases in merger activity are due to
managerial behavior and decisions. By analyzing the economic, political, and technological
landscapes as well as valuation and interest rate data during periods of intense merger
activity, I conclude that neoclassical theories are stronger in explaining the first three waves,
whereas behavioral theories are stronger in explaining the last three waves.
ACKNOWLEDGEMENTS
First and foremost, I would like to take this opportunity to thank both of my readers,
Professor Van Horn and Professor Batta, as well as Professor Pedace, for their guidance and
support throughout this process. I would also like to thank my parents for their endless love
and encouragement.
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TABLE OF CONTENTS
INTRODUCTION 3
LITERATURE REVIEW 4
THE NEOCLASSICAL VIEW 5 INDUSTRY SHOCK THEORY 5 THE Q-THEORY OF MERGERS 8 THE BEHAVIORAL VIEW 11 MARKET TIMING THEORY 12 AGENCY COST THEORY 15 MANAGERIAL DISCRETION THEORY 17
DATA AND RESULTS 19
A NEOCLASSICAL ANALYSIS, BY WAVE 21 A BEHAVIORAL ANALYSIS, BY WAVE 34
CONCLUSION 42
REFERENCES 45
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INTRODUCTION
Mergers and acquisitions (M&As) are part of “the market for corporate control” and
take place when one firm, the “acquirer”, takes over another firm, the “target”. Companies
merge in order to achieve “synergy”, the concept that the combined value of two companies
would be greater than the sum of the separate, individual companies due to the enhanced
cost efficiencies of the new business. By merging, the two companies combine resources
and therefore have a better chance of controlling the market and dominating their industry or
industries. Over the years, corporate mergers have occurred in waves, with periods of
intense merger activity followed by few transactions in the takeover market. For my thesis, I
will explore what causes these merger waves. More specifically, I will be looking at merger
waves in the United States, focusing on how these causes can affect the size of the merger
wave, the type of mergers that take place during that wave (horizontal, vertical, or
conglomerate mergers), and the industry or industries in which the mergers take place.
Mergers and acquisitions represent one of the most crucial activities in corporate
finance and have become an essential tool for corporate growth and development. In 2017,
the M&A market experienced $3.7 trillion in transaction volume, becoming the fifth most
active year on record (Cristerna, 2018). M&A’s possess many benefits that increase profits
and shareholder value through various strategies. These strategies include economies of
scale produced by increasing market share, the diversification of product and market risks,
capitalizing on the expanded use of an existing distribution network through the acquisition
of new product capabilities, and more (Tamosiuniene, 2009). There is currently debate
around the causes of merger waves. However, the existing literature tends to side with one
of two theories: The behavioral theory, which is the belief that merger waves are correlated
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with high stock market valuations and that they result from the timing of managers’ market
overvaluations of their firms (Harford, 2005), and the neoclassical theory, which argues that
merger waves are the result of industry shocks.
I examine data on historical merger waves and use these two different frameworks in
order to identify patterns and determine what actually drives merger waves. Since we are in
the midst of a merger wave, the new data could possibly help to identify a new pattern and
clarify the causes of these waves. Furthermore, because each merger wave is unique and
clusters by factors such as time, type, and industry, it will be valuable to further understand
what specific types of causes can lead to different types of merger waves. More specifically,
I look at whether these waves are caused by firms combining across different economies in
order to gain efficiency and capture bigger market shares, or if they are a result of managers
trying to increase profitability in the short run. By analyzing historical merger waves and the
economic, political, and technological changes going on during those time periods, we can
gain a better understanding of what drives merger waves in different economies or industries
over time.
LITERATURE REVIEW
Considerable research has been conducted on the causes of M&As and it is widely
acknowledged that merger waves exist. However, there is little research dedicated to
explaining merger waves. No consensus currently exists as to what actually drives these
waves. The existing literature tends to use one of two frameworks to analyze merger waves:
Neoclassical and behavioral. Within those two frameworks are different theories which
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explain the causes of merger waves. In this literature review, I will be explaining both of the
frameworks and their underlying theories, as well as providing evidence from existing
literature that supports these theories.
1. The Neoclassical View
The neoclassical view seeks rational explanations for the causes of merger waves and
assumes the separation of ownership and control, which means that the shareholders of a
company (the owners) have no direct control over management’s decision making. This
view also assumes that managers act to maximize shareholder value and/or capital market
efficiency. This framework stems from the empirical observation that changes in the
economy, which could be technical or regulatory, cause industries to consolidate in waves
(Mitchell & Mulherin, 1996). There are two main theories of the neoclassical framework:
The Industry Shock Theory and the Q-Theory of Mergers.
a. Industry Shock Theory: Theoretical Contributions
The industry shock theory posits that merger waves result from shocks to an
industry’s economic, technological, or regulatory environment (Harford, 2005). In
economics, a “shock” is defined as an unexpected or unpredictable event that affects an
economy, either positively or negatively. For example, shocks could be the development of
a new technology, a new fiscal or monetary policy, or even a new law being put into action.
Mitchell & Mulherin (1996) support this theory by finding interindustry restructurings and
takeovers are directly related to economic shocks in those industries. They isolated industry
shocks that drove merger activity during the fourth merger wave in the 1980’s, and studied
industry-level patterns in takeover and restructuring activity during that time, hypothesizing
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that corporate takeovers are often the least cost means for an industry’s structure to respond
to economic shocks.
Maksimovic & Phillips (2001) state that firms adjust in size until the marginal
benefit is equal to the marginal cost of production; as output prices increase, more
productive firms experience a larger gain in value from the assets that they control. As a
result, these firms find it optimal to acquire plants from less productive firms in the industry
even when that involves an increase in the costs of management (Maksimovic & Phillips,
2001). Similarly, they also find that a positive shock in an industry increases the opportunity
cost of operating as an inefficient producer in that same industry. Industry shocks alter the
value of assets and create incentives to transfer those assets to more productive uses.
Maksimovic & Phillips’s empirical results indicate that assets are more likely to be sold
when: (1) the economy is undergoing positive demand shocks, (2) when the assets are less
productive than their industry benchmarks, (3) when the selling firm has more productive
divisions in other industries, and (4) when the selling division is less productive
(Maksimovic & Phillips, 2001). When there is a positive demand shock, productive firms
seek to acquire the assets of less productive firms, whose lack of productivity in comparison
with its peers is exacerbated by the positive industry shock.
Gort (1969) states that mergers occur when two actions are satisfied: 1) a non-
owners’ estimated value of an asset must be higher than that of some owner of that asset,
and 2) the buyers’ investor surplus, which Gort defines as the difference between the
investor’s estimated value of the asset and its actual market price, must be greater than that
investor’s surplus for any other asset that they can buy. Therefore, according to Gort,
economic disturbances “alter the structure of expectations” (Gort, 1969) and create
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discrepancies in the valuations needed to produce mergers because they alter the
expectations of individuals, rendering the future less predictable and leading to an increase
in the variance in valuations. This variance in valuations is not a result of asymmetric
information, but instead a result of differing opinions on how an economic disturbance will
affect the value of a company. Since valuations are merely estimates and investors rely on
past records to predict future performance, when an economic shock occurs the past
becomes less effective in predicting the future and the range of estimates increases. This
leads to more variation and uncertainty in valuations. Using this framework, Gort claims that
changes in technology and fluctuations in stock prices lead to more M&A activity. When an
industry experiences a change in technology, this leads to new products or new processes of
production. Because demand for new products and production costs are now difficult to
predict from past performance, the variance in investors’ valuations increase and the
frequency of mergers also increase. When a company experiences a rapid change in its share
price, this new share price leads to increased variability in valuations. According to Gort,
positive and negative changes both increase valuation dispersion, but affect merger activity
in opposite ways: A price increase leads to a decrease in merger activity because acquirers
are less likely to buy overvalued companies, whereas a price decrease leads to an increase in
merger activity for the opposite reason.
Empirical Support
In support of the industry shock theory, Kleinert and Klodt (2002) examine the causes of
the five original merger waves in the 20th century. The first merger wave, which occurred
from 1897 to 1904, was caused by the industrial revolution and then ended with the
enforcement of the Sherman Act and Clayton Act. The act prevented the monopolization of
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industries and impeded horizontal merger activities, which is the merging of companies in
the same industry. In response to the new laws controlling horizontal mergers, a second
wave occurred from 1920 to 1929 and was dominated by vertical mergers (the merging of
companies involved at different stages of the supply chain process, ie: a car company
merging with a tire production company) and conglomerate mergers (the merging of
companies in completely unrelated industries).
The third wave lasted from 1965-1975 and was caused by the strive for economies of
scale via mass production in consumer goods industries, by acquiring firms in other markets
(aka: conglomerate mergers), and by the diversification of products. The fourth wave, which
lasted from 1984-1988, was less distinct in the US than in Europe because Europe was
preparing for the completion of the Single Market. As a result, firms tried to convert
“national champions” into international or European ones. In order to do so, firms aimed to
achieve synergies by merging production activities with related technologies, leading the
merger waves to be in technology-intensive industries. Lastly, Kleinert and Klodt (2002)
claim that the fifth wave, which started in 1995 and was still ongoing at the time of the
paper’s publication, was driven by globalization and deregulation because they observed
that the most active industries in that wave were 1) those where a globalized market was of
importance and 2) where deregulation and liberalization significantly impacted competition
intensity.
b. Q-Theory of Mergers: Theoretical Contributions
The Q-ratio is used to determine if a company is over or under valued and equals the
total market value of a company divided by its total asset value, or the total asset
Ching 9
replacement cost (Investopedia, 2003). The Q-theory of mergers draws from the Q-theory of
investment, which states that a firm’s investment rate should rise with its Q-ratio. A
company has a “low Q” if the Q-ratio is between 0 and 1. A low Q means that the
replacement cost of assets is greater than the value of the stock, so therefore the company is
undervalued. Conversely, if a company has a Q-ratio that is greater than 1, it is considered to
have a “high Q” and is overvalued.
Tobin’s Q theory suggests that the Q-ratio is a driving factor behind the investment
decisions of companies (Tobin, 1969). Companies with a high Q tend to be well managed,
can generate a return on capital that exceeds the cost of capital, and should invest in more
assets in order to maximize their shareholders’ value (Tobin, 1969). Therefore, high Q
companies tend to buy low Q companies, which pose as attractive investment opportunities.
Jovanovic and Rousseau (2002) expand on Tobin’s Q-theory and argue that high Q firms
tend to buy low Q firms because total takeover returns, or the combined values of the
merging firms, are larger if the target has a low Q and the acquirer has a high Q. In that
light, the Q-theory of mergers states that merger waves are a result of the effective
reallocation of assets that occurs when poorly managed companies (those with a low Q), are
acquired by better managed companies (companies with a high Q). Markets with widely
differing Q ratios lead to increased M&A activity and more mergers waves occur in those
markets.
Dong et al (2006) investigate the motivators for takeovers by considering empirical
relationships between the market valuations of firms and a set of takeover characteristics.
The authors test two different theories of takeovers: the misvaluation hypothesis, which is
behavioral rather than neoclassical, and the Q hypothesis of takeovers. The misvaluation
Ching 10
states that market inefficiencies have important effects on takeover activity. Bidders with
high valuations try to profit by buying undervalued targets with cash, or by paying equity for
targets that may be overvalued but still have a lesser value than the bidder. The Q hypothesis
of takeovers, on the other hand, focuses on how acquisitions redeploy assets and asserts that
takeovers reallocate the target’s assets to different uses. These uses can generate higher or
lower payoffs, depending on the business opportunities of the bidder and target firms, as
well as the quality of their management. According to this hypothesis, Q is an indicator of
the degree to which a firm can create shareholder value from their invested resources. High
quality bidders (high Q firms) improve bad targets (low Q firms) more than bad bidders
improve good targets. Dong et al (2006) establish that the evidence for the Q hypothesis is
stronger pre-1990, whereas the evidence for the misevaluation hypothesis is stronger post-
1990. This suggests that the Q hypothesis may be better in explaining merger waves that
occurred before 1990.
Empirical Support
In their paper, Jovanovic and Rousseau (2002) pooled approximately 118,000
observations from 1971-2000. They looked at Q, the market to book ratio of each acquiring
company, and q, the average market to book value of “disappearing” firms, or the acquired
firms. They examine the effect Q would have on X, a company’s direct investment in
capital, and how Q-q would affect Y, the acquisitions of the bundled capital. Their results
suggest that while the effect of Q on X was significant, the effect of Q-q, or the difference in
Q values between the acquirer and the target, had a significant impact on Y with nearly three
times that of Q on X. In addition, they also found that wider Q dispersions between
Ching 11
acquiring and target companies correlated with increased merger activity, therefore proving
that widely differing Q ratios lead to merger waves.
To test both the misevaluation and Q hypotheses, Dong et al (2006) used the ratio of
a firm’s price-to-book value of equity (or P/B) as a proxy for Q, and a firm’s price-to-
residual income (or P/V) as well as their P/B for the misevaluation hypothesis. Since P/B
and P/V provide complementary information about the misevaluation hypothesis, Dong et al
(2006) performed both univariate and multivariate tests. The authors studied approximately
1,000 successful and 800 unsuccessful acquisitions bids, then divided the ratios into bidder
P/B and P/V and target P/B and P/V. They found that bidder valuation ratios, on average,
were higher than those of their targets. From their sample of 2,916 firms for which they
could calculate P/B, the average P/B was 4.405 for acquirers and 1.159 for targets—
extremely statistically significant results. The bidder versus target findings are consistent
with the Q hypothesis. The Q hypothesis predicts that the total gains are generated by
acquisitions with “bad” targets (lower Q) and “good” bidders (higher Q) than by ones
involving good targets and bad bidders. Therefore, a higher bidder valuation and lower
target valuation are associated with high bidder and target returns, which also confirms
Jovanovic and Rousseau’s (2002) findings that wider dispersions in Q between the target
and bidding companies lead to increased merger activity.
2. The Behavioral View
Whereas the neoclassical view assumed that managers always strive to maximize
shareholder value and capital market efficiency, the behavioral view relaxes those
assumptions and proposes that there may be managerial motivation to engage in merger
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activity (Gugler et al, 2006). The behavioral view is supported by observations that stock
market valuations are positively correlated with aggregated merger and industry merger
activity. What separates the behavioral view from the neoclassical view is that managerial
behavior, rather than economic shocks, is what drives merger waves. Next, I discuss the
three main theories that make up the behavioral framework.
a. Market Timing Theory: Theoretical Contributions
According to the market timing theory, merger waves are driven by overvalued
markets that have valuation dispersion, and managers try to time these markets by using
their overvalued shares to acquire lesser valued companies and gain their real assets
(Lorenzen, 2015). The term “market timing” refers to financing decisions that are intended
to capitalize on temporary mispricings in the market, usually by issuing overvalued
securities and purchasing undervalued ones1. This is very similar to the misvaluation
hypothesis that we discussed earlier. Market timing reveals that while managers may have a
long-term view, they also consider short-term profitability and success, and therefore may
cater to short-term mispricing to further this objective (Baker et al., 2004).
Shleifer and Vishny (2003) present a model of M&As based on stock market
misvaluations of the combining firms. They theorize that transactions are driven by the stock
market valuations of merging firms and argue that financial markets are inefficient, causing
markets to incorrectly value companies during certain periods (Schleifer and Vishny, 2003).
They assume that management of both the acquiring and target companies are rational and
1 Baker, M., Ruback, R.S., Wurgler, J., 2004. Behavioral Corporate Finance: A Survey (Working
Paper No. 10863). National Bureau of Economic Research. https://doi.org/10.3386/w10863
Ching 13
fully informed about their company and industry, therefore they can recognize situations
when their company and other companies in the industry are incorrectly valued. Overall,
Schleifer and Vishny (2003) conclude that managers engage in M&A activity to protect
shareholders from long term wealth loss and exploit their temporarily overvalued stock to
acquire lesser companies. However, because their stock price is overvalued, the shareholders
of the acquiring company suffer a short-term loss from the decrease in value post-merger but
ultimately experience a long-term gain from the company’s acquisition of assets.
Rhodes-Kropf et al (2005) explore the effects of misvaluation on merger activity,
which is similar to the market timing theory. They focus on the market-to-book value of
equity ratios of companies, or M/B, and decompose it into three parts using the formula M/B
= M/V x B/V, V representing the value of a company. The three parts are firm-specific error,
time-series error, and long-run value to book. Acquirers with high firm-specific error use
stock to buy targets with relatively low firm-specific error at times when both firms benefit
from positive time-series selection error, or when both firms are overvalued in the market.
Additionally, merger intensity is highly positively correlated with short-run deviations in
valuation from long-run trends and that low long-run value-to-book (V/B) firms buy high
long run V/B targets when they control for firm-specific and time-series sector error.
Therefore, they claim that while it is generally true that higher M/B firms acquire lower M/B
firms, much of this is driven by short-run deviations in firm and sector level fundamentals.
They conclude that high short-run value but low long-run value firms may buy high
long-run value firms in order to substantiate the market’s beliefs and protect shareholders
from long term wealth loss, which agrees with the market timing theory. Though the
neoclassical Q theory suggests that successful transactions have large differences in M/B
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between the bidder and target, Rhodes-Kropf et al (2005) claim that failed transactions
actually have larger differences that completed transactions, while successful deals display
higher levels of misvaluation. Even in industries that have experienced an economic shock,
most acquirers in that industry come from the highest misvaluation quintile. Therefore, even
though economic shocks could be fundamental drives of merger activity, Rhodes-Kropf et al
believe that misvaluation affects how these shocks are spread throughout the economy.
Misvaluation affects the method of payment used to conduct transactions, as well as who
buys whom.
Empirical Support
Schleifer and Vishny’s (2003) model suggests that, since managers act on high
valuations in order to protect shareholders, the more highly valued acquirer would only
make a cash bid if the target was undervalued even at the bid price, ie: P < q, or the price is
less that the cost of capital. According to the authors, this is most likely to happen with
undervalued targets who experience low returns prior to being acquired. Adrade et al (2001)
supports them, finding that in 66% of mergers between 1973 and 1998, the value of the
acquiring company was greater than that of the target company.
Because the Market Timing theory suggests that managers act in the best interests of
shareholders, their model also suggests bidder returns from cash acquisitions should be
positive in the long run. Loughran and Vijh (1997) found that tender offers result in positive
abnormal bidder returns of 43% in the five years following the merger. Rau and Vermaelen
(1998) studied a larger sample of 316 tender offers between 1980-1991 and found that
acquirers in their study experienced positive long-run returns of 8.5% in the three years
following the merger, which supports Schleifer and Rhodes-Kropf et al’s findings.
Ching 15
Additional evidence comes from Rhodes-Kropf et al, who looked at 4,025 mergers and
found that the average log(M/B) of acquirers was 0.83 and the average log(M/B) of targets
was 0.69. They also found that the average long-run V/B of acquirers was 0.39, compared to
0.58 for the targets. This evidence therefore supports their claims that high M/B firms buy
low M/B firms and that firms with low long-run value tend to buy firms with high long-run
value.
b. Agency Cost Theory: Theoretical Contributions
Agency costs are costs that arise because of core problems such as conflicts of
interest between management and shareholders of a company. Shareholders want
management to run the company in a way that maximizes shareholder value, but
management might make decisions that maximize their personal wealth and power. Unlike
the market timing theory which assumes that managers of a company act in the interest of
their shareholders, the agency cost theory of M&As states that merger activity results from
managers acquiring firms for their own self-interests and motivations such as profit
maximization and job security (Cummings and Xie, 2008). There are multiple reasons why
M&As could benefit managers. Cummings and Xie (2008) believe managers may
intentionally acquire companies that require their personal skills, which would make it
harder for shareholders to replace them. Managers may also be motivated to engage in non-
value enhancing mergers in order to increase the size of their firm and their compensations.
Jensen (1986) adds to this, stating that growth of a company increases the amount of
resources under its control, therefore increasing managers’ power and compensation.
Additionally, the fact that firms tend to reward middle managers through promotions rather
Ching 16
than bonuses leads to a managerial bias towards growth through acquisitions, because
growing the company adds more positions and creates more opportunities for promotion
(Jensen, 1986). Therefore, M&As are motivated by managerial self-interest, and they are
unlikely to generate operating or financial synergies and valuations could decrease post-
merger.
In a later paper, Jensen (2005) explains that managers who act out of self-interest
only focus on short-term gains for their companies. Being a CEO, CFO, or manager of a
company with an overvalued stock is dangerous because a company cannot produce
performance that is required to justify that stock price, except by pure luck. The market
expects an overvalued company to keep outperforming in order to sustain their high
valuation. But since that is impossible, managers start to make decisions that destroy long-
run value of the company but generate the market’s expected performance in the short-run.
Despite knowing that they are unable to meet their market-projected growth, managers
pursue mergers that are potentially destructive to the company’s long-term value,
postponing the problem until they have left the company.
Empirical Support
In their study, Moeller et al (2005) provide evidence on the magnitude of the agency
costs of overvalued equity. They looked at 4,136 acquisitions from 1998 to 2001, 87 of
which were “large loss” deals that experienced significant losses post-merger. The aggregate
wealth loss associated with the large loss deals was $397 billion, while the other 4,049
acquisitions made a total gain of $157 billion. The acquiring firms lost a total of $240 billion
in comparison to a loss of $4.2 billion in all of the 1980’s. The authors also note that though
the large loss deals represented only 2.1% of acquisitions from 1998 to 2001, they accounted
Ching 17
for 43.4% of the money spend on acquisitions during that period. In addition, the losses to
bidders were offset by the gains to sellers for a net synergy gain of $11.5 billion in the
1980’s. However, from 1998-2001, the losses to acquirers exceeded gains to the target firms,
resulting in a net synergy loss of $134 billion.
Jensen (2005) also presents the case of Nortel, a real-life illustration of the agency
cost theory which shows that management was destroying value through the company’s
acquisitions. Between 1997 and 2001 Nortel was under the leadership of its new CEO, John
Roth. During this time, Nortel acquired 19 companies at a price of more than $33 billion and
paid for many of these acquisitions with Nortel stock, which increased dramatically during
that same period. When Nortel’s stock price collapsed, most of these acquisitions had to be
written off as losses (Jensen. 2005). Nortel’s effort to transform itself clearly damaged the
company and its shareholders. At the end of 2001, the company was valued at $24 billion
and its share price fell by more than 90% from its peak in September 2000. Nortel’s share
price was also 44% lower than it was on October 1, 1997, when Roth took over as CEO.
Jensen (2005) estimates that the agency cost of overvalued equity for Nortel, or the total loss
experienced by shareholders, was $44.5 billion. But, Nortel’s decline did not stop there—the
price drop suffered by Nortel didn’t just involve the elimination of its overvaluation, but it
also involved a significant destruction of its core value, mainly through acquisitions and
overinvestment (Jensen, 2005).
c. Managerial Discretion Theory: Theoretical Contributions
The third and final of the behavioral theories is the managerial discretion theory, or the
managerial theory. This theory is similar to the agency cost theory and its assumption that
Ching 18
managers act in their own self-interest, but it states that managers pursue to grow their firms
through mergers either because their incomes are tied to growth or because they get
“psychic income” from managing a large firm (Gugler et al., 2012). Psychic income is
defined as the nonmonetary or nonmaterial satisfactions one gets from an occupation or
economic activity, such as the feeling of being powerful or important (Financial Times
Lexicon).
According to Gugler et al. (2012), merger waves occur during stock market booms
because optimism in the market allows growth-seeking managers to undertake more wealth-
destroying mergers than under normal conditions. These managers pursue growth through
M&A activity even though it may not be in the best interest of their shareholders, and it is
shown that report weak or negative effects of mergers on the profitability and sales of
companies (Gugler et al., 2012). Under the behavioral view, the common “shock” that
causes a merger wave is the increase in optimism in the market, which leads to a stock
market boom.
The past two behavioral theories hypothesized that merger waves are caused by
managers’ reactions to overvalued stock prices, which only accounts for mergers financed
through stock. As a solution, Gugler et al. (2012) offers the managerial theory, which covers
different financing options. It states that firms that are not overvalued may still undergo
mergers when optimism in finance markets is high, choosing to finance the merger with cash
or issue debt. Therefore, when optimism in equity markets increases, the market’s constraint
weakens on managers who wish to grow their companies through mergers that destroy
shareholder wealth. As a result, more mergers take place and a merger wave occurs.
Ching 19
Conclusion
In summary, the extant literature does not reach a consensus. The research on M&As
is extensive, but there is little research on the actual causes of merger waves. Also, much of
the literature is older and refers to the 20th century merger waves. As we are now in the
midst of a merger wave, new data could possibly help identify a new pattern and clarify the
causes of the current waves. My contribution to the existing literature will be to isolate the
cause of merger waves, whether it agrees with the aforementioned theories or not.
DATA AND RESULTS
If one considers the total number of M&A transactions that have occurred
throughout history, they would find that M&A activity is highly cyclical and occurs in
waves. As shown in Figure 1, a total of six completed merger waves have occurred since the
1880’s and we are currently in the midst of a seventh wave. Figure 2 focuses on the last four
merger waves, showing the number of M&A transactions in North America since 1980
compared to the total value of M&A transactions by year compared to GDP for that year.
Ching 20
Figure 1- Merger waves in the US from 1851-2017 (estimated)
Figure 2- Total M&A in North America vs. Value of transactions as a percent of GDP
In order to explain this cyclical pattern in M&A activity and relate it to neoclassical
theories, I first look at each individual wave and the shocks that occurred in the
corresponding time period (regulatory and political changes, technological advances, and
0
2000
4000
6000
8000
10000
12000
14000
16000
18000
1888
1893
1898
1903
1908
1913
1918
1923
1928
1933
1938
1943
1948
1953
1958
1963
1968
1973
1978
1983
1988
1993
1998
2003
2008
2013
Num
ber
of
Tra
nsa
ctio
ns
Source: Thomson Financial, Institute for Mergers, Acquisitions and Alliances (IMAA) analysis.
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
35.00%
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
18,000
20,000
19
86
19
88
19
90
19
92
19
94
19
96
19
98
20
00
20
02
20
04
20
06
20
08
20
10
20
12
20
14
20
16
20
18 V
alu
e o
f Tr
ansa
ctio
ns
as %
of
GD
P
Nu
mb
er o
f Tr
ansa
ctio
ns
Number of M&A
Value as % of GDP
Source: Thomson Financial, Institute for Mergers, Acquisitions and Alliances (IMAA) analysis.
Ching 21
economic shocks). Then, I analyze the last three waves by looking at valuations and interest
rates during those periods in order to relate it to behavioral theories. As previously
mentioned, there is no consensus on the exact cause of these waves, but the literature tends
to side with either the neoclassical view or the behavioral view. Through my combination of
analyses, I hope to provide my own explanation on the causes of these waves.
I. A Neoclassical Analysis, by Wave
The First Wave: 1896-1903
The first merger wave came to be known as the “great merger movement” and was
comprised of mostly horizontal mergers that consolidated the manufacturing industry. At
this time in history, the US had just come out of The Panic of 1893 and was experiencing a
period of economic prosperity. In addition, the US was going through a period of
industrialization and reform which created opportunities in the manufacturing industry
though technological innovation. The invention of the steam engine led to the creation of a
well-developed national railroad network which allowed the US to exploit high scale
economies and removed many of the physical constraints on businesses, allowing them to
expand their distribution channels all over the US (Keinert and Klodt, 2002; Banerjee &
0
200
400
600
800
1000
1200
189
0
189
1
189
2
189
3
189
4
189
5
189
6
189
7
189
8
189
9
190
0
190
1
190
2
190
3
190
4
190
5
Num
ber
of
Mer
ger
s
The First Merger Wave: 1896-1903
Ching 22
Eckard, 1998). Also around this time, the New York Stock Exchange (NYSE) was
experiencing its largest trading volumes to date due to revolutionary technological
developments such as the telephone, which reduced trading time from 15 minutes to 6
seconds (Reference for Business). This increase in trading volume reflected the rise of large
corporations and industry wide trusts, reaching a high of 3 million shares in 1901. As a
result, stock prices during this period were a reasonable reflection of a firm’s performance
and could therefore provide information on the future prospects of the firm, including
potential mergers (Banerjee & Eckard, 1998).
In 1890, Congress passed the Sherman Antitrust Act, which outlawed monopolistic
business practices in the US. However, in 1895, the supreme court decision in the E.C.
Knight case placed the mergers of manufacturing firms outside the reach of the act and
therefore outside the jurisdiction of Federal regulation. Therefore, there were no legal
barriers to mergers which led to an increase in merger activity during this time (Banerjee &
Eckard, 1998). In addition, antitrust enforcement reached an all-time low during the
Mckinley Presidency from 1897-1901. This lack of restraint allowed firms to consolidate
into industrial trusts with market shares so large that they exceeded 80% in many cases
(Banerjee & Eckard, 1998). According to O’Brien (1988), this merger wave was a
temporary acceleration in the growth of firm size and industrial concentration. O’Brien
(1988) also claims that this wave was motivated by horizontal concentration in order to
suppress price competition.
In 1904, the Supreme Court overturned the previous E.C. Knight ruling in the
Northern Securities case and nullified a merger between two railroad companies, citing
concern that the resulting market dominance would negatively affect competition. Mergers
Ching 23
for all monopolies were now under Federal Law (Banerjee & Eckard, 1998). This change in
regulation, as well as the stock market crash of 1904, caused a slowdown in M&A activity
and ended the first merger wave.
The Second Wave: 1916-1933
The second merger wave was mainly comprised of oligopolistic mergers in the
banking sector. According to White (1985), this merger movement was one of the most
important developments in banking. During this period, many regulatory changes were
occurring. In 1913, the Federal Reserve Bank was established. In 1914, World War I broke
out and America became a global lender, replacing London as the center of the financial
world. Then, in November of 1918, the National Bank Consolidation act was passed and
established a formal procedure for the consolidation of national banks. Prior to the act, if
two national banks wanted to merge one had to be liquidated while the other purchased its
assets and assumed its liabilities (White, 1985). After this act was passed, merging was more
flexible; rather than having to fully liquidate, two national banks could consolidate under
either’s charter, they just had to specify the amount of capital, surplus, and undivided profits
0
200
400
600
800
1000
1200
1400
Num
ber
of
Mer
ger
s
The Second Merger Wave: 1916-1933
Ching 24
in the new merged organization and which assets would be eliminated, if any. This act only
applied to mergers between two national banks and a national bank wanting to merge with a
state bank still had to go through the old procedures. As a result, leading national banks
started abandoning their national charters to merge with state banks, which prompted the
creation of the McFadden Act of 1927. This act allowed a national bank to consolidate with
a state bank under the new rules, encouraging more mergers in the banking industry (White,
1985).
Additionally, in response to the Sherman Act of 1980 which banned the formation of
monopolies through horizontal mergers, the Clayton Act in 1914 encouraged vertical
mergers and the formation of oligopolies (Owen, 2006). This act served as a catalyst for the
second merger wave, which could be seen in the banking industry. According to White
(1985), banks during this time period needed bigger loans in order to continue serving their
industrial customers, a group that was increasing rapidly. Since loans were capped at 10% of
a company’s capital, banks turned to mergers as a quick way of increasing their capital in
order to increase their loan sizes. Once earnings from commercial loans started to decline,
these banks had to seek new ways to maintain and increase their income and moved into the
trust and investment banking businesses through vertical mergers, which allowed them to
quickly acquire the expertise and reputation necessary for success.
After the end of WWI, the Wilson administration put “unconventional handcuffs” on
the banking sector by establishing the World War Foreign Debts Commission Act in 1922,
which insisted that all debtor countries pay back their war loans to America (Investopedia).
This caused a slowdown in world trade and created hostility toward American goods. Then
in September of 1929, the stock market crashed on what is infamously known as Black
Ching 25
Tuesday and the world economy was knocked out, leading to the Great Depression in
October. The Fed could not contain the crash and refused to stop the Depression. All banks
suffered as a consequence, therefore ending the second merger wave.
The Third Merger Wave: 1960-1975
The third merger wave is often characterized as a wave of conglomerate mergers.
After World War II ended in 1945, the US emerged from the war as the world’s richest and
most militarily powerful country. The overall economy grew 37% during the 1950s and by
the end of the decade, the average family had 30% more purchasing power than in the
beginning. The US stock market rose significantly (Owen, 2006). As a result of this new
economic prosperity, profitable companies found themselves with large cash flows. Because
they didn’t want to pay out this extra money to shareholders via dividends, they instead
turned to the market for corporate control and reinvested the money back into their
businesses by acquiring other companies. However, as these firms sought to expand, they
also faced tougher antitrust enforcement from the government. In 1950, the Celler-Kefauver
Act was passed, which strengthened the anti-merger provisions of the Clayton Act and
0
1000
2000
3000
4000
5000
6000
7000
Num
ber
of
Mer
ger
s
The Third Merger Wave: 1960-1975
Ching 26
addressed loopholes. Now, the government was scrutinizing horizontal and vertical mergers
and companies that wanted to expand found their only option was to form conglomerates
(Gaughan, 2017).
As Owen (2006) notes, the number of conglomerate firms increased from 8.3% of
Fortune 500 firms in 1959 to 18.7% in 1969. Conglomerate mergers offer a means of
diversification for companies—for example, General Electric is a conglomerate and has a
number of businesses under its name such as healthcare, transportation, and energy. This
diversification serves as a method for companies to reduce cash flow volatility through
reducing exposure to industry specific risks (Nouwen, 2011). Therefore, during this time
many companies paid for their acquisitions using stock and opted for conglomerate mergers
so they could expand into new markets and areas and reduce risk. This third wave ended
with the 1973 oil crisis, when the members of the Organization of Arab Petroleum Exporting
Countries targeted the US, amongst other countries, by proclaiming an oil embargo and
severely increasing the price of oil per barrel. As a result of this crisis, there was a sharp
increase in inflation and a worldwide economic downturn, halting all merger activity.
The Fourth Wave: 1980-1990
0
1000
2000
3000
4000
5000
6000
7000
8000
Num
ber
of
Mer
ger
s
The Fourth Merger Wave: 1980-1990
Ching 27
During the 1980’s people started to see economic reforms as burdensome to
economic growth, and US financial sector resultantly experienced a lot of deregulation. At
this same time, there were a lot of innovative compensation schemes being established for
top executives (Santomero, 2003). These schemes included a significant increase in the use
of stock options as compensation, which was supposed to improve management’s incentives
to increase shareholder value. Many people argue that such compensation schemes placed
more emphasis on short term rather than long term performance and could have also
possibly led to managerial greed and mergers that would solely increase management’s
compensation. In order to increase valuations, more innovative compensation programs
were also put into place in order to encourage executives to take greater risks and engage in
more creative accounting in order to improve their reported earnings and drive their bottom
line. Management started to promote an aggressive corporate culture and no one held these
companies in check.
Due to this aggressive corporate culture, most of the bids in the fourth merger wave
were hostile, meaning that they did not have the approval of the target company’s
management (Nouwen, 2011) and that companies relied on aggressive and innovative
financial and legal techniques to acquire target companies and secure voting control
(Cheffins, 2015). This new wave was also characterized by “bust-up takeovers”, or
takeovers where large fractions of the target company’s assets were sold post-acquisition.
According to Goldstein (2000), some believe that hostile takeovers served as a form of
corporate governance because the threat of takeover would exert pressure on corporate
managers to act in the interest of shareholders. Financial market pressure should motivate
poorly performing management to do better, as well as function to discipline and replace
Ching 28
inefficient managers. While companies used cash and stock to finance M&As in the
previous waves, mergers in the fourth wave were leveraged buyouts (LBOs) and were
heavily financed by debt (Nouwen, 2011). Therefore, the fourth merger wave was comprised
of hostile takeovers because poor managerial incentive schemes combined with equally
ineffective corporate governance mechanisms allowed corporate mismanagement to flourish
throughout 1970-1980 (Owen, 2006). However, this wave came to an end due to the early
1980’s recession and a slowdown of the debt market, which dried up financing for these
mergers.
The Fifth Wave: 1993-2000
The 1990’s were seen as a decade of great economic prosperity. After the 1990-1991
recession, financial markets were booming and the globalization process accelerated
(Nouwen, 2011). In order to keep up with economic growth and increasing global demand,
U.S. companies targeted companies abroad and the number of cross-border acquisitions
increased significantly. This wave was less distinct in the US than in Europe, which is
shown by its small size in Figure 1. Also, Figure 3 shows that the number of M&A
transactions in Europe far surpassed those in the US in 1999 and 2000, even reaching one of
6000
8000
10000
12000
14000
16000
1993 1994 1995 1996 1997 1998 1999 2000 2001
Num
ber
of
Mer
ger
s
The Fifth Merger Wave: 1993-2000
Ching 29
its highest peaks in 2000. During this time, Europe was preparing for the creation of the
Single Market, which allowed all countries involved to trade with each other without
restrictions or tariffs. In response, countries tried to convert their strongest firms into
international competitors, merging their production activities with related technologies and
causing M&A activity to take place in technology intensive industries (Kleinert & Klodt,
2002).
Figure 3- Number of M&A Transactions in Europe vs. US
According the Nouwen (2011), the fifth wave began as a result of technological
innovations such as information technology, as well as a refocus of companies on their core
competencies in order to gain competitive advantage. US corporations wanted to participate
0
2000
4000
6000
8000
10000
12000
14000
16000
18000
20000
19
85
19
86
19
87
19
88
19
89
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
20
05
20
06
20
07
20
08
20
09
20
10
20
11
20
12
20
13
20
14
20
15
20
16
20
17
20
18
(O
ct 2
2)
20
18
(Fo
reca
st)
Nu
mb
er o
f M
&A
dea
ls
Europe US
Source: Thomson Financial, Institute for Mergers, Acquisitions and Alliances (IMAA) analysis.
Ching 30
in the globalization of the economy, which led to the creation of “mega” deals—such as
Exxon and Mobil and Citibank and Travelers—that were unthinkable before this wave.
Gaughan (2001) claims that the fifth wave trended towards consolidating mergers where
leading firms acquired competitors across the nation in order to build dominant companies.
According to Gaughan, most of these mergers were in the banking and telecommunications
industry, spurred on by significant changes in the regulatory environment at the time. In
2000, the dot com bubble burst and the stock market fell tremendously, losing 10% of its
value within a few weeks. This marked the end of the fifth wave.
The Sixth Wave: 2001-2008
The sixth merger wave began after the 2001 recession. At this time, economic
growth was resurfacing and there was an increase in liquidity into the market due to the
stimulus from the Federal Reserve which kept interest rates low in order to stimulate the
economy. Low interest rates also contributed to the rise of private equity funds as levered
acquisitions became cheaper and the stock market was booming, leading to large amounts of
available capital and an extremely favorable environment for M&As (Cordeiro, 2014).
Alexandridis et al (2012), believe that behavioral theories which state that mergers happen
6000
7000
8000
9000
10000
11000
12000
13000
14000
15000
2001 2002 2003 2004 2005 2006 2007 2008 2009
Num
ber
of
Mer
ger
s
The Sixth Merger Wave: 2001-2008
Ching 31
when overvalued firms seek to acquire less overvalued assets are unlikely to explain what
drove the sixth wave. They claim that stock prices during this wave were not overvalued and
were based on sound fundamentals rather than over-optimistic expectations. To support their
claim, they provide data that valuations were lower in 2003-2007 than they were during the
1990’s wave (Alexandridis et al, 2012). Therefore, it is most likely that the sixth wave was
mainly the result of the availability of abundant liquidity at the time. In contrast, Cordeiro
(2014) believes that the high liquidity and cheap capital generated distortions and target
companies ended up being overvalued due to enormous speculation and a lack of detected
risks from directing a large volume of resources towards “bad” assets.
However, both authors agree on the economic downturns that ended the wave. In late
2007, investors and corporate managers started becoming skeptical of Mortgage Backed
Securities (MBSs) and credit markets. Then in 2008, credit dried up and financing became
scarce, leading the world into recession and bringing M&A activity to a halt (Alexandridis et
al, 2012; Corderio, 2014).
The Seventh Wave: 2010-Present
9000
10000
11000
12000
13000
14000
15000
16000
Num
ber
of
Mer
ger
s
The Seventh Merger Wave: 2012-Present
Ching 32
The seventh wave is the most current merger wave. Since coming out of the Great
Recession in 2009, the US economy has been growing. Interest rates are low but starting to
increase once again, stock prices are at historic highs, and the unemployment rate is at a 49-
year low of 3.7%, with job openings exceeding the number of unemployed Americans by
more than 650,000 (Morath, 2018). As seen in Figure 4, GDP has climbed $5.1 trillion
dollars since 2009, and is expected to increase another $0.6 trillion by the end of 2018.
Figure 5 shows that corporate profits are currently at an all-time high due in part to tax cuts
(Grocer, 2018), indicating that firms have more money to spend and re-invest in their
businesses.
In its 2018 M&A trends report, Deloitte states that corporations now have more spending
firepower; companies say that their cash levels have increased and that M&A remains the
number one intended use of those funds (Deloitte, 2018). Technology acquisition is the
number one driver of M&A pursuits this year and managers are showing a strong bias
towards vertical integration, especially in life sciences, health care, technology, and financial
services.
Figure 4- US GDP from 2000-2018 (estimated)
Source: U.S. Bureau of Economic Analysis, Real Gross Domestic Product [GDPC1], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/GDPC1, October 29, 2018.
13.0 13.8 14.5 14.7 14.4 15.0 15.5 16.2 16.8 17.5 18.2 18.7 19.5 20.1
0.0
5.0
10.0
15.0
20.0
25.0
GD
P (
$ i
n t
rill
ion
s)
Ching 33
Figure 5- US Quarterly Corporate Profits, since Q3 2015
According to the New York Times, fears of Silicon Valley’s growing ambitions
helped to drive a record run of M&A activity, with more than $2.5 trillion in mergers
announced during the first half of 2018 (Grocer, 2018). In addition, four of the ten biggest
deals during this period were made in part to fend off competition from the largest
technology companies as the value of acquisitions announced during the first half of 2018
increased 61% from the same time in 2017 (Grocer, 2018). Companies are turning to M&As
in order to capture a greater market share and change their business models in order to battle
companies such as Netflix, Amazon, and other tech companies who are currently trying to
enter new industries. Along the same lines, a number of larger deals have been in the media
and healthcare industries—industries that are having to battle tech’s encroachment upon
their territories. Large media firms are now having to compete with companies like Netflix
by owning both their content and the platform on which it is provided, and healthcare
companies must respond to companies like Amazon who are trying to enter the healthcare
business.
1665.1
1578.21610.8
1632.2 1631.6
1693.9 1707.81733.7 1735.9
1816.8
1965.22007.5
1500
1600
1700
1800
1900
2000
2100
$ (
bil
lio
n U
SD
)
Source: TradingEconomics.com, US Bureau of Economic Analysis
Ching 34
II. A Behavioral Analysis, by Wave
A common theme that underlies all behavioral theories is that merger waves are driven
by managerial behavior and decisions rather than economic shocks. Another driver of these
theories is that market valuations are positively correlated with merger activity. However,
valuation data, such as a company’s stock price, is unavailable for the older merger waves.
Therefore, I will only consider the valuations of mergers within the last three waves. The
Buffet Indicator, Warren Buffet’s favorite market valuation tool, is calculated by dividing
the total market capitalization (aka market cap) of the S&P 500 by US Gross GDP. A
company’s market cap is defined as its number of shares outstanding multiplied by its stock
price. According to Buffet, the higher this ratio, the more overvalued the market currently is.
Figure 6 contains the Wilshire 5000 to GDP ratio as compared to quarterly M&A volumes
over time for the last three merger waves. The Wilshire 5000 to GDP ratio is identical to
The Buffet Indicator, but uses the total market cap of the Wilshire 5000 index in the
numerator rather than the S&P 500.
Figure 6- Wilshire 5000 to GDP ratio vs. M&A Volume, Quarterly
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
0
500
1000
1500
2000
2500
3000
3500
4000
4500
1/1
/85
6/1
/86
11/1
/87
4/1
/89
9/1
/90
2/1
/92
7/1
/93
12/1
/94
5/1
/96
10/1
/97
3/1
/99
8/1
/00
1/1
/02
6/1
/03
11/1
/04
4/1
/06
9/1
/07
2/1
/09
7/1
/10
12/1
/11
5/1
/13
10/1
/14
3/1
/16
8/1
/17
Wil
shir
e 5
00
0/
GD
P r
atio
Nu
mb
er o
f M
&A
# M&A
Wilshire
5000/GDP
Sources: Federal Reserve Bank of St. Louis: Wilshire 5000 Full Cap Price Index; Federal Reserve Bank of St. Louis: US Gross Domestic Product, Thomson Financial, Institute for Mergers, Acquisitions and Alliances
Ching 35
I chose to use the Wilshire 5000 index because it includes all US stocks with readily
available pricing, covering a wider variety of companies in different industries with different
market caps than other stock indices. As shown in Figure 6, the Wilshire 5000/GDP ratio
and M&A volume are positively correlated; as the ratio increases, so does M&A activity.
This suggests that high market valuations drive mergers and acquisitions. As stated in the
Market Timing Theory, if market valuations are high, managers are more likely to use their
companies’ inflated stock prices to acquire the real assets of lower-priced companies.
Interest rates also have an impact on valuations, driving merger waves. According to
Warren Buffet, the higher the interest rate, the greater the downward pull on financial
valuations. This is because the rates of return that investors need from any kind of
investment are directly tied to the risk-free rate that they can earn from government
securities. If the government rate rises, the prices of all other investments must adjust
downward to a level that brings their expected rates of return into line.
Figure 7- Federal Funds Rate vs. Number of M&A transactions in the US
0.001.002.003.004.005.006.007.008.009.0010.00
02,0004,0006,0008,000
10,00012,00014,00016,00018,000
198
6
198
8
199
0
199
2
199
4
199
6
199
8
200
0
200
2
200
4
200
6
200
8
201
0
201
2
201
4
201
6
201
8
Fed
eral
Fund
s R
ate
(%)
Num
ber
of
Tra
nsa
ctio
ns
Number of M&A
Federal funds rate
Source: Federal Reserve Bank of St. Louis: Effective Federal Funds Rate; Thomson Financial, Institute for Mergers, Acquisitions and Alliances (IMAA) analysis.
Ching 36
Conversely, if interest rates fall, the decrease pushes the prices of all other
investments upward. When perceived valuations are high, even if those valuations may be
rational, managers might choose to take advantage of their highly valued shares and engage
in merger activity. Therefore, if we assume that high valuations encourage more M&A
activity, we can conclude that as interest rates decrease, the number of M&A transactions
increase. This is shown in Figure 7, which compares the number of M&A transactions in the
US with the federal funds rate. When the federal funds rate is high, M&A activity is low.
Additionally, Figure 7 shows that low federal funds rates occur at the same time as the start
of each of the last three merger waves, indicating that low interest rates are positively
correlated with an increase in merger activity.
Ching 37
Values of Companies Pre and Post Merger
Though high valuations and interest rates indicate that merger waves are driven by
managerial reactions to good market conditions, they do not tell us about the motives behind
managers’ decisions to engage in M&A activity. In order to gain insight into this, I consider
the major M&A transactions that have taken place during the past three merger waves. By
“major,” I mean the most publicized mergers at the time with transaction values above $20
billion. More specifically, I was interested in examining the effect that the transaction had
on the total value of the company. I considered the market caps of acquiring companies in
each wave one month pre and post-combination to see if the merger had a positive or
negative effect on the company’s total market cap. If the value of a company declined post-
merger, then this could suggest that the merger was driven by managerial greed such as
increasing firm size to increase one’s compensation, regardless of the effect the merger
would have on shareholders.
On the other hand, if the value of the company increased, then this could confirm that
managers engage in mergers to maximize shareholder wealth. Tables 1-3 below present data
on the “biggest”, or highest value, completed M&A transactions that have occurred in the
US during the last three merger waves. More specifically, it shows the percent change in the
market caps of the acquiring companies pre and post-merger. In these mergers, either the
acquiring company was from the US, the target company was from the US, or both were
from the US. As stated before, valuation data is difficult to find before these waves, which
removes them from consideration.
Ching 38
Table 1— The Fifth Wave (1993-2000)
Acquirer Target
Year
merged Mkt cap pre
Mkt cap
post
%
Change
Worldcom MCI Communications 1997 NA NA NA
Exxon Mobil 1998 174.95 267.08 53%
Citicorp Travelers Group 1998 7.48 4.87 -35%
Bell Atlantic GTE 1998 76.93 119.22 55%
BP Amoco 1998 81.64 79.84 -2%
Vodafone Group Mannesmann 1999 44.8 163.15 264%
Pfizer Warner Lambert 1999 167.67 285.48 70%
SBC Communications Ameritech Corp 1999 96.40 99.96 4%
Vodafone group Airtouch communications 1999 33.98 37.37 10%
Note: Market cap is in Billions, taken one month pre and post-merger
Table 2—The Sixth Wave (2001-2008)
Acquirer Target
Year
merged
Mkt cap
pre
Mkt cap
post
%
Change
America Online Inc Time Warner 2000 224.00 20.00 -91%
Comcast Corp
AT&T Broadband & Internet
Svcs 2001 35.01 41.12 17%
Pfizer Inc Pharmacia Corp 2002 176.48 262.81 49%
JPMorgan Chase &
Co Bank One Corp,Chicago,IL 2004 140.82 139.19 -1%
AT&T Inc BellSouth Corp 2006 100.68 99.53 -1%
InBev NV Anheuser-Busch Cos Inc 2008 205.66 165.88 -19%
Pfizer Inc Wyeth 2009 110.82 146.78 32%
Glaxo Wellcome SmithKline Beecham Plc. 169.93 158.64 -7%
Ching 39
Table 3—The Seventh Wave (2009-Current)
Acquirer Target
Year
merged
Mkt cap
pre
Mkt cap
post
%
Change
Verizon Communications Inc Verizon Wireless Inc 2013 144.280 134.880 -7%
T-Mobile US Metro PCS 2013 4 14.77 269%
Berkshire Hathaway Heinz 2013 273.49 290 6%
Softbank Sprint 2013 35.55 44.79 26%
Heinz Kraft 2015 43.21 97.48 126%
Actavis PLC Allergan Inc 2015 76.39 115.95 52%
Fortis ITC Holdings 2016 8.7 12.7 46%
IMS Health Holdings Quintiles Transnational Holdings 2016 9.07 18.7 106%
TransCanada Columbia Pipeline Group 2016 29.1 37.03 27%
Johnson Controls Tyco International 2016 26.9 38.08 42%
Microsoft Linkedin 2016 470.18 484.05 3%
Baxalta Shire 2016 36.86 55.85 52%
Anheuser-Busch InBev SAB Miller 2016 205.66 165.88 -19%
Charter Communications Inc Time Warner Cable Inc 2016 20.81 22.66 9%
Sherwin Williams Valspar 2017 31.17 32.79 5%
Northstar Asset Management
Group
Northstar Realty Finance &
Colony Capital 2017 1.7 8 371%
Abbott Laboratories St Jude Medical 2017 56.57 74.11 31%
The Dow Chemical Co DuPont 2017 78.67 167.55 113%
Dell EMC Corp 2017 13.65 16.06 18%
Century Link Level 3 Communications 2017 14.93 13.13 -12%
Great Plain's Energy Westar Energy 2018 7.55 15.1 100%
Marriott International Starwood Group 2018 45.6 44.95 -1%
AT&T Time warner 2018 198.35 227.01 14%
Marathon Petroleum corp Andeavor 2018 37.11 48 29%
Keurig Green Mountain Dr. Pepper Snapple Group 2018 21.67 33.15 53%
As shown in Table 1 and 3, the majority of the acquiring companies in the fifth and
seventh waves experienced an increase in value post-merger. However, as shown in Table 2,
the majority of acquiring companies in the sixth wave experienced a decrease in value post-
merger, which could indicate that mergers in that wave were driven by managerial greed.
Considering the macroeconomic events during the sixth wave, the US had just emerged
Ching 40
from the 2001 recession. Interest rates were low and there was excess money in the market
due to the stimulus from the Federal Reserve. Finding themselves with a sudden abundance
of liquidity, managers at this time could have participated in mergers solely to increase their
compensation or power, rather than maximize shareholder value. This greed could also be a
result of the corporate climate at the time, which is reflected in the use of risky investment
vehicles such as the Mortgage-Backed Security—the faulty asset-backed security that was a
major contributor to the 2008 recession.
In contrast, the economic environments during the fifth and seventh wave are
similar, which could explain why values of acquiring companies increased post-merger
during those waves. In both the fifth and seventh wave, the US economy was expanding,
and companies are looking to expand in order to stay competitive. For example, companies
during the fifth wave merged in order to counteract the increasing globalization, while
companies during the seventh wave are currently merging in order to counteract tech giants
such as Amazon and Netflix. Additionally, both waves were spurred by technological
innovations—the development of information technology in the fifth wave and the threat
and expansion of Silicon Valley in the seventh wave. In order to build dominant and
competitive companies, managers must have a long term view when making M&A
decisions. Therefore, it is more likely that managers approached M&A transactions in these
two waves with the intention to build the company and increase its value post-merger rather
than increasing their own returns.
Ching 41
III. Results
After examining the economic environments during the seven merger waves, it
seems as if the first three merger waves were caused as a result of macroeconomic shocks,
whereas the last three waves were driven by managers’ responses to high market valuations.
For the fourth wave, it appears it was a result of managerial self-interest, reflected in
aggressive corporate culture and the hostile takeovers during the period. However, since
valuation data is not available for mergers during that time frame, I am unable to empirically
test my conclusion.
Each of the first three waves acted as responses to economic changes during wave
preceding it: The first merger wave consisted of horizontal mergers in the manufacturing
industry and was spurred by technological inventions from the industrial revolution as well
as a changing regulatory environment, including a loophole in the Sherman Antitrust Act.
The second wave was a response to the regulations of the first wave that banned horizontal
mergers and was mainly comprised of oligopolistic mergers. Lastly, with the government
cracking down on both vertical and horizontal mergers, the third wave therefore consisted of
conglomerate mergers. In contrast, market valuations were high and interest rates were low
during the last three merger waves which could have caused managers to engage in merger
activity in order to increase firm size and maximize either shareholder wealth or their own
returns. Therefore, this is evidence that neoclassical theories may best explain the causes of
the first three merger waves while behavioral theories best explain the last three merger
waves.
Ching 42
CONCLUSION
In order to determine what drives merger waves, I explored the neoclassical and
behavioral theories by analyzing a multitude of economic shocks and trends that occurred
during each merger wave. To find data that aligned with neoclassical theories, I analyzed
previous economic, political, technological, and regulatory changes that were occurring
during each time period to see if those changes acted as shocks that caused an increase in
merger activity. For the behavioral theory, I focused on market valuations and interest rates
in relation to M&A activity in order to determine if the market was overvalued in times of
heavy merger activity. Finally, for the last three waves, I looked at the total market
capitalization of acquiring firms pre and post-merger during to see if the merger had created
or destroyed value for the firms, which could yield insight into managerial motives for
participating in mergers.
Ultimately, I concluded that neoclassical theories are better for explaining the first
three waves while behavioral theories are better for the last three waves. So, while industry
shocks and economic changes may have caused the first three waves, the last three waves
were driven by high market valuations and managers’ decisions to use their company’s
overvalued stock to acquire companies and expand their businesses. Interestingly, it seems
as if the sixth wave was driven by managerial greed—which is shown in Table 2 by an
overall loss in value post-merger—while the fifth and seventh waves appear to be driven by
managers’ efforts to maximize shareholder value. The fourth wave, however, was a wave
consisting of hostile takeovers during a time of increased deregulation and use of stock-
based compensation. Therefore, I hypothesize that managerial behavior was the cause of this
Ching 43
wave, but I am unable to test my hypothesis since valuations during that period were
unavailable to me, given the resources I had access to.
My findings on what drives merger waves is important because there is a lack of
literature surrounding the topic and no consensus currently exists. While there are
discussions on M&As themselves and the motivation behind mergers, there is very little
research on the cyclical pattern of merger activity and the actual fundamental causes of
merger waves. Since we are currently in the midst of the seventh wave, which is a wave that
has lasted for eight years, we need to be cautious. As my macroeconomic research shows, all
previous waves ended in an economic crisis or recession. When there is a negative shock to
the economy, consumer confidence decreases, which consequently decreases market
valuation. Based on my research, when valuations start to decrease so does M&A activity,
bringing the merger wave to an end.
One major limitation to my research was the lack of valuation data for companies
before 1990. Since many companies that merged were not public before that time, it was not
possible to find data on stock price or the number of shares outstanding, and therefore I was
unable to calculate their market caps. There was also limited data on mergers during the fifth
and sixth wave, which limited the extent to which I could study the values of companies pre
and post-merger. As seen in tables 1 and 2, I only had nine mergers to sample for both of
those waves, which is not a representative sample. Additionally, since I only studied the
biggest M&A transactions in each wave, the data is not representative of all mergers that
took place during the period
If I had more time and resources to create an optimal study for this topic, I would
create aggregate indicators of both the neoclassical and behavioral theories (ie: indicators for
Ching 44
the Q-theory, agency cost theory, market timing theory, etc). By looking at the sum of each
indicator during each wave, we would be able to better understand the drivers behind each
wave and whether they side with the neoclassical theory or behavioral theory. I also would
look for more commonly used measures of elevated market sentiment (investors’ attitudes
towards the market) at the aggregate level (all industries combined). With these measures, I
would analyze the extent to which they explain the volume of transactions in a given year,
and whether those transactions weigh more heavily in years of merger waves. Lastly, I
would use past data to predict where we are in the latest merger wave given our current
economic state. By doing so, we could predict if we are now at the top of the merger wave,
or on the downside, which could signal that we are close to another economic contradiction.
Ching 45
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